Periods of trading where prices are outside expected ranges often garner regulatory attention. Additionally, many abusive trading strategies involve executions at unusual prices. Firms that have executions during such events or have patterns of unusual executions are more likely to attract regulatory attention for lapses in supervisory controls or even disruptive trading practices.
Traditional trade surveillance tools rely on single points of reference to detect unusual prices, such as last execution or previous closing price, leading to excessive false positives around significant market movement.
The Neurensic Suspicious Price Movement model detects outliers by evaluating execution prices both before and after a potentially unusual trade and assigning significance to each of these reference executions based upon its time and price proximity. This method dramatically reduces the incidence of false positives and focus attention upon periods of real risk.